Fraud Detection

Customer Retention

Digital Marketing

Customer Retention

Reduce churn and create more effective customer relationships

The easiest way to grow your revenue is to keep your existing customers happy. It can cost up to five times as much to acquire a new customer, as it does to retain an existing one. Nurturing your existing customers yields far better sales results with a success rate of 60-70% selling to existing customers compared to 5-20% selling to a new customer.

US companies lose $136.8 billion per year due to churn- and, it’s avoidable. 33% of customers consider changing providers after even one instance of bad customer service. Getting something wrong not only hurts you, but it sends your customers to your opposition.

Retain your customers, increase your profits

CyborgIntell can transform customer relationships, help retain customers and increase sales. Not only can AutoAI and machine learning identify customer churn before it happens, but it can help increase sales to existing customers and increase customer satisfaction.

Preventing churn becomes simple, using data to not only see past history of why customers have left, but also identifying new patterns and trends as they happen. Churn patterns hide deeply complex behaviours, but within a few hours, iTuring AutoAI can accurately predict customers at risk of leaving. This means that preventive steps can be taken to retain them. iTuring AutoAI recognises when a model is degrading and can automatically trigger an alert to assess and implement a new model, ensuring the platform is always making highly accurate predictions.

See how AI can improve customer retention in the real world

A bank needed to improve their merchant retention rate. Much of their income was derived from money remittance facilitated from merchants, and high churn was decreasing their income. They needed to identify which merchants were at risk of leaving, so they could take corrective action before it happened.

iTuring AutoAI built a predictive model using a number of factors, and this quantified the likelihood of the merchant’s churn the following month. This model predicted, with 92% accuracy, how likely a merchant was to leave. Not only was this client attrition list highly accurate in predicting who may leave, but it also reduced false positives, saving employee time spent on unneeded retention efforts.

Within forty minutes, the bank had a list of customers to target. Identifying drivers of churn allowed steps to be implemented to reduce and minimise the loss of customers. Dropping the churn rate by 10% increased their revenue by US$2,000,000 in the next quarter.

How CyborgIntell can transform your customer engagements

iTuring AutoAI provides advanced model evaluation techniques, adequate visualytics and explainable models that allow business users to better understand their clients churn behaviour so that they can implement actionable and impactful retention strategies.